Optimisation of cutting in primary wood transformation industries
Abstract: The loss of raw
materials in wood cutting industries has reached high proportions (30 to 36% of
volume yield, Ngolle Ngolle, 2009). The purpose of this paper is to solve the
problem of optimising the production on the basis of the commercial value of
the cuts.
Design/methodology/approach: In order to tackle this problem, we started
with the generalities on the exploitation and the primary conversion of wood in
Cameroon. After that, we studied the various methods of cutting and the different
products obtained. We then proceeded with the formulation of the log cutting
optimisation problem based on a real shape model of the logs, objective of
research works presented in (Danwé, Bindzi, Meva’a & Nola, 2011). We
finally completed our work with the design and the presentation of a software
package called cutting optimiser.
Findings: We start by having some knowledge on the geometry of the logs,
cutting strategies and classification of cuts. This classification enables us
to determine the quality and quantity of the production, and to estimate the
commercial value of the log. The solution to this problem then led to the
design of a software package.
Research limitations/implications: In this paper, the optimisation
problem concerns problems where the objective function is non-explicit, the
variables discreet, and the constraints non-explicit.
Practical implications: The solution to this problem then led to the
design of a software package to be used as a cutting optimiser. The automation
of the cutting operation leads to an accelerated work and an increase in the
volume of the cuts produced daily.
Originality/value: This research is among the few to solve discrete
optimization problems with constraints. Some constraints concerning the
mechanical characteristics of the logs are taken into account. The constraints
can equally be non-explicit. Moreover the market standards impose technological
constraints which render the problem of optimisation even more complex.
Author: Raïdandi Danwe, Isaac
Bindzi, Lucien Meva'a
Journal Code: jptindustrigg120010
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